基于数字孪生的产品生命周期绿色制造新模式
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摘要
随着人们可持续发展意识的增强,传统制造业正深刻重塑并向绿色化、智能化、服务化转型。制造企业相继运用各种先进信息化技术(云计算、信息物理系统、物联网、仿真建模)来解决可持续制造中的各类问题,由此提出数字孪生驱动的绿色制造新模式,围绕以绿色特征为中心的物理世界与虚拟世界的交互与融合,建立了包含绿色特征的五维数字孪生模型,以重塑绿色制造过程中物理实体、虚拟孪生体、数据、交互接口、服务五维要素之间的关系及要素的绿色特性。分析了五维数字孪生模型下绿色材料选择、绿色拆解、绿色回收、绿色再制造及逆向供应链领域的相关应用,最后以基于绿色特征提取的产品生命周期能耗管理平台验证了提出的五维数字孪生体驱动的产品生命周期绿色制造新模式。
With the increasing enhancement of people's consciousness of sustainable development,the traditional manufacturing industry is deeply remolding and transforming into green,intelligent and service-oriented.Manufacturing enterprises had successively applied various advanced information technology(cloud computing,CPS,IoT,simulation modeling)to solve various problems in sustainable manufacturing.With the integration of physical world and virtual world centered on green features,a new paradigm of digital twin driven green manufacturing was proposed,and a five-dimensional digital twin model with green features was established to reconstruct the relationship between physical entities,virtual twins,data,interactive interfaces,services and the green characteristics of elements in green manufacturing process.Then,the application of green material selection,green disassembly,green recycling,green remanufacturing and reverse supply chain under the five-dimensional digital twin model were analyzed.The energy consumption management platform of product life cycle based on energy consumption feature extraction was validated.
With the increasing enhancement of people's consciousness of sustainable development,the traditional manufacturing industry is deeply remolding and transforming into green,intelligent and service-oriented.Manufacturing enterprises had successively applied various advanced information technology(cloud computing,CPS,IoT,simulation modeling)to solve various problems in sustainable manufacturing.With the integration of physical world and virtual world centered on green features,a new paradigm of digital twin driven green manufacturing was proposed,and a five-dimensional digital twin model with green features was established to reconstruct the relationship between physical entities,virtual twins,data,interactive interfaces,services and the green characteristics of elements in green manufacturing process.Then,the application of green material selection,green disassembly,green recycling,green remanufacturing and reverse supply chain under the five-dimensional digital twin model were analyzed.The energy consumption management platform of product life cycle based on energy consumption feature extraction was validated.
引文
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[30]ZHUANG Cunbo,LIU Jianhua,XIONG Hui,et al.Connotation,architecture and trends of product digital twin[J].Computer Integrated Manufacturing Systems,2017,23(4):753-768(in Chinese).[庄存波,刘检华,熊辉,等.产品数字孪生体的内涵,体系结构及其发展趋势[J].计算机集成制造系统,2017,23(4):753-768.]
[31]SCHROEDER G N,STEINMETZ C,PEREIRA C E,et al.Digital twin data modeling with AutomationML and a communication methodology for data exchange[J].IFAC-PapersOnLine,2016,49(30):12-17.
[32]SCHROEDER G,STEINMETZ C,PEREIRA C E,et al.Visualising the digital twin using web services and augmented reality[C]//Proceedings of the 2016IEEE 14th International Conference on Industrial Informatics(INDIN).Washington,D.C.,USA:IEEE,2016:522-527.
[33]LUO W,HU T,ZHANG C,et al.Digital twin for CNC machine tool:modeling and using strategy[J].Journal of Ambient Intelligence and Humanized Computing,2018,10(3):1-12.
[34]TUEGEL E J,INGRAFFEA A R,EASON T G,et al.Reengineering aircraft structural life prediction using a digital twin[J].International Journal of Aerospace Engineering,2011.DOI:10.1155/2011/154798.
[35]WANG X V,WANG L.Digital twin-based WEEE recycling,recovery and remanufacturing in the background of Industry4.0[J].International Journal of Production Research,2018,55:1-11.
[36]XIANG F,HUANG Y,ZHANG Z,et al.Research on ECBOM modeling and energy consumption evaluation based on BOM multi-view transformation[J].Journal of Ambient Intelligence and Humanized Computing,2019,10(3):953-967.
[37]ZYO Y,TAO F,NEE A Y C.An Internet of things and cloud-based approach for energy consumption evaluation and analysis for a product[J].International Journal of Computer Integrated Manufacturing,2018,31(4/5):337-348.
[2]TAO F,ZHANG L,LAILI Y.Configurable intelligent optimization algorithm:design and practice in manufacturing[M].Berlin,Germany:Springer-Verlag,2014.
[3]XIANG Feng,HUANG Yuanyuan,ZUO Ying,et al.SLA oriented energy efficiency evaluation of manufacturing service[J].China Mechanical Engineering,2018,29(20):2401-2407,2415(in Chinese).[向峰,黄圆圆,左颖.面向服务水平等级协议的制造服务能效评估[J].中国机械工程,2018,29(20):2401-2407,2415.]
[4]LIU Fei,CAO Huajun,HE Naijun.Research status and development trend of green manufacturing[J].China Mechanical Engineering,2000,11(S1):114-119(in Chinese).[刘飞,曹华军,何乃军.绿色制造的研究现状与发展趋势[J].中国机械工程,2000,11(S1):114-119.]
[5]SONG Shouxu,LIU Ming,KE Qingdi,et al.Components optimization design for remanufacturing based on residual strength[J].Journal of Mechanical Engineering,2013,49(9):121-127(in Chinese).[宋守许,刘明,柯庆镝,等.基于强度冗余的零部件再制造优化设计方法[J].机械工程学报,2013,49(9):121-127.]
[6]XIN Lanlan,JIA Xiujie,LI Fangyi,et al.Green feature modeling for mechanical and electrical product conceptual design[J].Computer Integrated Manufacturing Systems,2012,18(4):713-718(in Chinese).[辛兰兰,贾秀杰,李方义,等.面向机电产品方案设计的绿色特征建模[J].计算机集成制造系统,2012,18(4):713-718.]
[7]DEIF A M.A system model for green manufacturing[J].Journal of Cleaner Production,2011,19(14):1553-1559.
[8]JIANG Z,ZHANG H,YAN W,et al.An evaluation model of machining process for green manufacturing[J].Advanced Science Letters,2011,4(4/5):1724-1728.
[9]JIANG Z,ZHANG H,SUTHERLAND J W.Development of multi-criteria decision making model for remanufacturing technology portfolio selection[J].Journal of Cleaner Production,2011,19(17/18):1939-1945.
[10]LI Congbo,ZHU Yantao,LI li,et al.Multi-objective CNCmilling parameters optimization model for energy efficiency[J].Journal of Mechanical Engineering,2016,52(21):120-129(in Chinese).[李聪波,朱岩涛,李丽,等.面向能量效率的数控铣削加工参数多目标优化模型[J].机械工程学报,2016,52(21):120-129.]
[11]DATTOMA V,GIANCANE S,NOBILE R,et al.Fatigue life prediction under variable loading based on a new non-linear continuum damage mechanics model[J].International Journal of Fatigue,2006,28(2):89-95.
[12]HAO H,ZHANG Q,WANG Z,et al.Forecasting the number of end-of-life vehicles using a hybrid model based on grey model and artificial neural network[J].Journal of Cleaner Production,2018,202:684-696.
[13]DU Yanbin,CAO Huajun,LIU Fei,et al.Evaluation of machine tool remanufacturing scheme based on entropy weight and AHP[J].International Journal of Computer Integrated Manufacturing,2011,17(1):84-88(in Chinese).[杜彦斌,曹华军,刘飞,等.基于熵权与层次分析法的机床再制造方案综合评价[D].计算机集成制造系统,2011,17(1):84-88.]
[14]GOEPP V,ZWOLINSKI P,CAILLAUD E.Design process and data models to support the design of sustainable remanufactured products[J].Computers in Industry,2014,65(3):480-490.
[15]TAO F,ZUO Y,DA XU L,et al.Internet of Things and BOM-based life cycle assessment of energy-saving and emission-reduction of products[J].IEEE Transactions on Industrial Informatics,2014,10(2):1252-1261.
[16]ONDEMIR O,GUPTA S M.Quality management in product recovery using the Internet of Things:An optimization approach[J].Computers in Industry,2014,65(3):491-504.
[17]XIA K,GAO L,WANG L,et al.A semantic information services framework for sustainable weee management toward cloud-based remanufacturing[J].Journal of Manufacturing Science and Engineering,2015,137(6):061011.DOI:10.1115/1.4030008.
[18]WANG L,WANG X V,GAO L,et al.A cloud-based approach for WEEE remanufacturing[J].CIRP Annals-Manufacturing Technology,2014,63(1):409-412.
[19]WANG L,TORNGREN M,ONORI M.Current status and advancement of cyber-physical systems in manufacturing[J].Journal of Manufacturing Systems,2015,37(2):517-527.
[20]PAROLINI L,SINOPOLI B,KROGH B H,et al.A cyberphysical systems approach to data center modeling and control for energy efficiency[J].Proceedings of the IEEE,2012,100(1):254-268.
[21]JIANG Z,JIN Y,E M,et al.Method of tasks and resources matching and analysis for cyber-physical production system[J].Advances in Mechanical Engineering,2018,10(5):1687814018777828.
[22]TAO Fei,LIU Weiran,LIU Jianhua,et al.Digital twin and its potential application exploration[J].Computer Integrated Manufacturing Systems,2018,24(1):1-18(in Chinese).[陶飞,刘蔚然,刘检华,等.数字孪生及其应用探索[J].计算机集成制造系统,2018,24(1):1-18.]
[23]GRIEVES M.Digital twin:manufacturing excellence through virtual factory replication[EB/OL].[2018-02-23].https://research.fit.edu/media/site-specific/researchfitedu/camid/documents/1411.0_Digital_Twin_White_Paper_Dr_Grieves.pdf.
[24]TAO F,ZHANG M,LIU Y,et al.Digital twin driven prognostics and health management for complex equipment[J].CIRP Annals,2018,67(1):169-172.
[25]TAO Fei,ZHANG Meng,CHENG Jiangfeng,et al.Digital twin workshop:a new paradigm for future workshop[J].Computer Integrated Manufacturing Systems,2017,23(1):1-9(in Chinese).[陶飞,张萌,程江峰,等.数字孪生车间---一种未来车间运行新模式[J].计算机集成制造系统,2017,23(1):1-9.]
[26]TAO F,ZHANG M.Digital twin shop-floor:a new shopfloor paradigm towards smart manufacturing[J].IEEE Access,2017,5:20418-20427.
[27]TAO F,CHENG J,QI Q,et al.Digital twin-driven product design,manufacturing and service with big data[J].The International Journal of Advanced Manufacturing Technology,2018,94(9/10/11/12):3563-3576.
[28]TAO Fei,ZHANG Meng,CHENG Jiangfeng,et al.Digital twin workshop:a new paradigm for future workshop[J].Comput Integrated Manufacturing System,2017,23(1):1-9(in Chinese).[陶飞,张萌,程江峰,等.数字孪生车间-一种未来车间运行新模式[J].计算机集成制造技术,2017,23(1):1-9.]
[29]TAO Fei,CHENG Ying,CHENG Jiangfeng,et al.Theories and technologies for cyber-physical fusion in digital twin shop-floor[J].Computer Integrated Manufacturing Systems,2017,23(8):4-12(in Chinese).[陶飞,程颖,程江峰,等.数字孪生车间信息物理融合理论与技术[J].计算机集成制造系统,2017,23(8):4-12.]
[30]ZHUANG Cunbo,LIU Jianhua,XIONG Hui,et al.Connotation,architecture and trends of product digital twin[J].Computer Integrated Manufacturing Systems,2017,23(4):753-768(in Chinese).[庄存波,刘检华,熊辉,等.产品数字孪生体的内涵,体系结构及其发展趋势[J].计算机集成制造系统,2017,23(4):753-768.]
[31]SCHROEDER G N,STEINMETZ C,PEREIRA C E,et al.Digital twin data modeling with AutomationML and a communication methodology for data exchange[J].IFAC-PapersOnLine,2016,49(30):12-17.
[32]SCHROEDER G,STEINMETZ C,PEREIRA C E,et al.Visualising the digital twin using web services and augmented reality[C]//Proceedings of the 2016IEEE 14th International Conference on Industrial Informatics(INDIN).Washington,D.C.,USA:IEEE,2016:522-527.
[33]LUO W,HU T,ZHANG C,et al.Digital twin for CNC machine tool:modeling and using strategy[J].Journal of Ambient Intelligence and Humanized Computing,2018,10(3):1-12.
[34]TUEGEL E J,INGRAFFEA A R,EASON T G,et al.Reengineering aircraft structural life prediction using a digital twin[J].International Journal of Aerospace Engineering,2011.DOI:10.1155/2011/154798.
[35]WANG X V,WANG L.Digital twin-based WEEE recycling,recovery and remanufacturing in the background of Industry4.0[J].International Journal of Production Research,2018,55:1-11.
[36]XIANG F,HUANG Y,ZHANG Z,et al.Research on ECBOM modeling and energy consumption evaluation based on BOM multi-view transformation[J].Journal of Ambient Intelligence and Humanized Computing,2019,10(3):953-967.
[37]ZYO Y,TAO F,NEE A Y C.An Internet of things and cloud-based approach for energy consumption evaluation and analysis for a product[J].International Journal of Computer Integrated Manufacturing,2018,31(4/5):337-348.